2018
DOI: 10.1016/j.tcs.2018.03.002
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Polynomial-time algorithms for computing distances of fuzzy transition systems

Abstract: Behaviour distances to measure the resemblance of two states in a (nondeterministic) fuzzy transition system have been proposed recently in the literature. Such a distance, defined as a pseudo-ultrametric over the state space of the model, provides a quantitative analogue of bisimilarity. In this paper, we focus on the problem of computing these distances. We first extend the definition of the pseudo-ultrametric by introducing discount such that the discounting factor being equal to 1 captures the original def… Show more

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Cited by 4 publications
(1 citation statement)
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References 29 publications
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“…e fuzzy C-means clustering algorithm is a transformation method that uses membership to determine the size of clusters [21]. ere are two important parameters which are the number of clusters c and the fuzzy weighting index m.…”
Section: Fuzzy Algorithmmentioning
confidence: 99%
“…e fuzzy C-means clustering algorithm is a transformation method that uses membership to determine the size of clusters [21]. ere are two important parameters which are the number of clusters c and the fuzzy weighting index m.…”
Section: Fuzzy Algorithmmentioning
confidence: 99%